From Noon Reports to High-Frequency Sensors: Evaluating Data Sources for Digital Twin Simulations
By Zachary Tessler, Director of Data Science
The shipping industry is facing enormous pressures to decarbonize and must do so while preserving bottom lines. While noon reports have been an industry standard for decades, new data collection methods such as high-frequency data sensors have given owners and operators unparalleled amounts of data. This study evaluated Data Science metrics that measure the accuracy of simulations built with three types of data sets: i) models based on noon reports only; ii) models based on high-frequency sensor data; and iii) models based on a combination of a vessel’s noon reports enriched with high-frequency sensor data from similar vessels in the Nautilus data pool. The paper found that while models built on high-frequency sensor data yield the most accurate simulations, if high-frequency data is not available, results from noon-only models can be greatly improved by enrichment with similar vessels’ sensor data.
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